In [1]:
import pandas as pd
import numpy as np
import plotly.express as px
In [2]:
file = pd.read_csv("vaccination-data.csv")
In [3]:
file1 = file.loc[:, "COUNTRY"]
In [4]:
file2 = file.loc[:, "TOTAL_VACCINATIONS"]
In [5]:
file3 = file.loc[:, "WHO_REGION"]
In [6]:
file4 = file.loc[:, "TOTAL_VACCINATIONS_PER100"]
In [7]:
file5 = file.loc[:, "VACCINES_USED"]
In [8]:
df = {"Country": file1,
      "Total Vax": file2,
      "WHO Region": file3,
      "Total Vax Per 100 People": file4,
      "Vax Used": file5}
In [9]:
data = pd.concat(df, axis = 1)
In [10]:
#Bubble chart
fig = px.scatter(data, x = "Country", y = "Total Vax",
size = "Total Vax", color = "Country",
hover_name = "Country", log_x = False, size_max = 50)
fig.show()
In [11]:
#Sunburst chart. Inner Circle is WHO Region. Outer circle is number of vaccines
fig = px.sunburst(data, path = ["WHO Region", "Country", "Total Vax"], values = "Total Vax Per 100 People", color = "Vax Used")
fig.show()
In [15]:
!jupyter nbconvert --to html Vax_Numbers_By_Country.ipynb

[NbConvertApp] Converting notebook Vax_Numbers_By_Country.ipynb to html
[NbConvertApp] Writing 4244196 bytes to Vax_Numbers_By_Country.html
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